Design of Intelligent Detection System for Network Security Vulnerabilities Based on Knowledge Graph
The intelligent detection of network security vulnerabilities relies on a large amount of real data for analysis,and re-dundant and abnormal data can lead to a decrease in detection accuracy.In order to ensure the stable operation of network systems,a network security vulnerability intelligent detection system design based on knowledge graph is proposed.The network security vulner-ability detector from three aspects of the structure,logical model,and operation mode is designed to achieve the hardware design of the intelligent network security vulnerability detection system.The system software design collects security vulnerability data through web crawlers,removes redundant data and abnormal data,identifies security vulnerability entities according to attribute information,and obtains security vulnerability attribute information relationships.Based on this,it defines the representation form of the security vulnerability knowledge graph,designs the security vulnerability knowledge graph structure,and the construction and visualization of security vulnerability knowledge graph are realized;Based on the above network design results,an overall architecture for intelligent detection of the network security vulnerabilities is constructed to develop the specific process for the intelligent detection of the net-work security vulnerabilities,and obtain the final intelligent detection results of the network security vulnerabilities.The experimen-tal results show that under different experimental conditions,the minimum network security vulnerability detection rate of the de-signed system after application is 1.23％,the maximum F1 value of the network security vulnerability detection is 9.50,and the mini-mum response time of the network security vulnerability detection is 1 ms,confirming that the designed system has a optimal security vulnerability detection performance.
万方数据
维普
